Inertial Microfluidic Cell Stretcher (iMCS): Fully Automated, High‐Throughput, and Near Real‐Time Cell Mechanotyping. Issue 28 (23rd May 2017) - Deng, Yanxiang; Davis, Steven P.; Yang, Fan; Paulsen, Kevin S.; Kumar, Maneesh; Sinnott DeVaux, Rebecca; Wang, Xianhui; Conklin, Douglas S.; Oberai, Assad; Herschkowitz, Jason I.; Chung, Aram J.
Abstract : Mechanical biomarkers associated with cytoskeletal structures have been reported as powerful label‐free cell state identifiers. In order to measure cell mechanical properties, traditional biophysical (e.g., atomic force microscopy, micropipette aspiration, optical stretchers) and microfluidic approaches were mainly employed; however, they critically suffer from low‐throughput, low‐sensitivity, and/or time‐consuming and labor‐intensive processes, not allowing techniques to be practically used for cell biology research applications. Here, a novel inertial microfluidic cell stretcher (iMCS) capable of characterizing large populations of single‐cell deformability near real‐time is presented. The platform inertially controls cell positions in microchannels and deforms cells upon collision at a T‐junction with large strain. The cell elongation motions are recorded, and thousands of cell deformability information is visualized near real‐time similar to traditional flow cytometry. With a full automation, the entire cell mechanotyping process runs without any human intervention, realizing a user friendly and robust operation. Through iMCS, distinct cell stiffness changes in breast cancer progression and epithelial mesenchymal transition are reported, and the use of the platform for rapid cancer drug discovery is shown as well. The platform returns large populations of single‐cell quantitative mechanical properties (e.g., shear modulus) on‐the‐fly with high statistical significances, enabling actual usages in clinical and biophysical studies. Abstract : A novel inertial microfluidic cell stretcher capable of characterizing and classifying large populations of single‐cell deformability near real‐time in a fully automated manner is presented. Through this method, statistically robust cell deformability measurements in breast cancer progression and epithelial mesenchymal transition are reported, and the platform usage for cancer drug discovery is also demonstrated.